Chapter5solution.pptx

5. Risk, return, and the historical record

Instructor: Seongcheol Paeng

7/4/2020

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Problem Sets (Paraphrase with your own words.)

Explain Determinants of the Level of Interest Rates.

1) The supply of funds from savers, primarily households. 2) The demand for funds from businesses to be used to finance investments in plant, equipment, and inventories (real assets or capital formation). 3) The government’s net demand for funds as modified by actions of the Federal Reserve Bank. 4) The expected rate of inflation.

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2. Explain the Equilibrium Real Rate of Interest.

The government and the central bank (the Federal Reserve) can shift these supply and demand curves either to the right or to the left through fiscal and monetary policies. For example, consider an increase in the government’s budget deficit. This increases the government’s borrowing demand and shifts the demand curve to the right, which causes the equilibrium real interest rate to rise to point E′. The Fed can offset such a rise through an expansionary monetary policy, which will shift the supply curve to the right.

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3. Tax bracket: 20%, nominal return: 10%, Inflation rate: 6%

before-tax real rate: 10-6=4%

after-tax real return: 4%(1 − .2) = 3.2%

after-tax nominal return: 10%(1 − .2) = 8%

after-tax real interest rate: 8% − 6% = 2%

it = 6% × .2 = 1.2%

after-tax real return- after-tax real interest rate-it=? 3.2-2-1.2=0%

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Problem Sets (Paraphrase with your own words.)

4. Explain Sharpe Ratio.

The importance of the trade-off between reward (the risk premium) and risk (as measured by standard deviation or SD) suggests that we measure the attraction of a portfolio by the ratio of its risk premium to the SD of its excess returns. This reward-to-volatility measure was first used extensively by William Sharpe and hence is commonly known as the Sharpe ratio. It is widely used to evaluate the performance of investment managers. Sharpe ratio = Risk premium / SD of excess return (5.18)

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5. Explain Normal Distribution.

Figure 5.3 shows a graph of the normal curve with mean of 10% and standard deviation of 20%. A smaller SD means that possible outcomes cluster more tightly around the mean, while a higher SD implies more diffuse distributions. The likelihood of realizing any particular outcome when sampling from a normal distribution is fully determined by the number of standard deviations that separate that outcome from the mean. Put differently, the normal distribution is completely characterized by two parameters, the mean and SD.

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6. Explain Skew and Kurtosis.

A measure of asymmetry called skew is the ratio of the average cubed deviations from the sample average, called the third moment, to the cubed standard deviation. Cubing deviations maintains their sign (the cube of a negative number is negative). When a distribution is “skewed to the right,” as is the dark curve in Figure 5.4A, the extreme positive values, when cubed, dominate the third moment, resulting in a positive skew. When a distribution is “skewed to the left,” the cubed extreme negative values dominate, and skew will be negative.

Another potentially important deviation from normality, kurtosis, concerns the likelihood of extreme values on either side of the mean at the expense of a smaller likelihood of moderate deviations. Figure 5.4B superimposes a “fat-tailed” distribution on a normal distribution with the same mean and SD. Although symmetry is still preserved, the SD will underestimate the likelihood of extreme events: large losses as well as large gains.

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